PROJECT SUMMARY The misuse of and addiction to opioids is an epidemic in the U.S. that now reduces U.S. life expectancy. Overdose is the leading cause of premature death among Americans under the age of 50. More than 2 million Americans struggle with an opioid use disorder (OUD). Buprenorphine-naloxone, naltrexone, and methadone are all FDA-approved medications for OUD (MOUDs) that decrease opioid use and mortality and are the gold- standard of care. At this time, however, fewer than 20% of patients with OUD receive those treatments. We do not have a functioning system to treat OUD. Innovation to the way that we deliver OUD treatment could provide the OUD care we now need. Our team works with colleagues at Massachusetts Department of Public Health to investigate the OUD epidemic in MA and also recently convened a national stakeholder conference to identify feasible action plans for the OUD epidemic. What is clear is that state policy makers seek evidence to inform system-level change. System-level thinking investigates how systems operate and how they can be modified to produce desired outcomes. At this time, system-level data about OUD treatment are very limited and inconsistent. Simulation models integrate data from multiple sources to translate outcomes from clinical studies to policy-relevant data about population health and cost. A model that simulates the population with OUD in a state can be used to investigate delivery system innovations and project the impact on public health outcomes and cost and will be invaluable in the fight against OUD. Our goal is to inform state-level innovation for low- barrier access to MOUDs. Our objective is a five-year research program, Researching Effective Strategies to Prevent Opioid Death (RESPOND), that will develop a simulation model of OUD treatment and use it to inform system-level change. Our specific aims are: Aim 1: To develop and validate a state-level, population simulation model of OUD treatment and OUD care delivery. To build the simulation, we will leverage the MA ?chapter 55? dataset, a first-in-the-nation administrative records registry to study OUD. Aim 2: To develop priorities for delivering low-barrier access to MOUDs and identify epidemiologic and economic factors that should drive priorities at the state-level. We will investigate the benefits and cost of six models for implementing low-barrier access to MOUDs. We will identify innovations that provide the greatest benefit given available resources, and thereby develop priorities for policy. Aim 3: To simulate state-level regulations that govern insurance coverage for MOUDs to investigate how regulatory change could be coupled to innovation in OUD care delivery. We will simulate changes including requiring payers to reimburse MOUD treatment, prohibiting cost-sharing, and eliminating prior-authorization. Our team assembles national leaders in addiction medicine, simulation modeling, healthcare policy, and health economics to apply the power of simulation models to the OUD epidemic. Our innovative work will make RESPOND a national resource to inform a new kind of OUD care.